STDP Pattern Onset Learning Depends on Background Activity

Spike-timing dependent plasticity is a learning mechanism used extensively within neural modelling. The learning rule has previously been shown to allow a neuron to learn a repeated spatio-temporal pattern among its afferents and respond at its onset. In this study we reconfirm these previous results and additionally adduce that such learning is dependent on background activity. Furthermore, we found that the onset learning is unstable when in a noisy framework. Specifically, if the level of background activity changes during learning the response latency of a neuron may increase and with the adding of additional noise the distribution of response latencies degrades. Consequently, we present preliminary insights into the neuron's encoding: viz, that a neuron may encode the coincidence of spikes from a subsection of a stimulus' afferents, but the temporal precision of the onset response depends on some background activity, which must be similar to that present during learning.